Efficient exploration of unknown environments is a fundamental precondition for modern
autonomous mobile robot applications. Aiming to design robust and effective robotic …

When it comes to some essential abilities of autonomous ground vehicles (AGV), detection
is one of them. In order to safely navigate through any known or unknown environment, AGV …

Agricultural robots are one of the important means to promote agricultural modernization
and improve agricultural efficiency. With the development of artificial intelligence technology …

We present a novel method for reliable robot navigation in uneven outdoor terrains. Our
approach employs a fully-trained Deep Reinforcement Learning (DRL) network that uses …

This work reports ondeveloping a deep inverse reinforcement learning method for legged
robots terrain traversability modeling that incorporates both exteroceptive and proprioceptive …

Understanding the terrain in the upcoming path of a ground robot is one of the most
challenging problems in field robotics. Terrain and traversability analysis is a …

Despite the rapid advancement of navigation algorithms, mobile robots often produce
anomalous behaviors that can lead to navigation failures. The ability to detect such …

This paper presents a new synthetic dataset obtained from Gazebo simulations of an
Unmanned Ground Vehicle (UGV) moving on different natural environments. To this end, a …

Autonomous navigation in agricultural environments is challenged by varying field
conditions that arise in arable fields. State‐of‐the‐art solutions for autonomous navigation in …

Inertial sensing is used in many applications and platforms, ranging from day-to-day devices
such as smartphones to very complex ones such as autonomous vehicles. In recent years …